Skip to Main content Skip to Navigation
Poster communications

Flood forecasting with machine Learning, data Assimilation and Semi-pHysical modeling

Abstract : ANR FLASH project (2009-2013) intends to capitalize on the advantages of machine learning methods in order to provide tools for real-time flash floods forecasting. In a first step, water level forecasts were provided based on rain estimation of rainfalls, leading to the design of a demonstrating software. In a second step, weather RADAR measurements will be taken in advantage, as for rainfall estimation than for directly inputs reflectivity to the model. Comparison between the 3-type of inputs (rain gauge rainfall, RADAR rainfall, COMEPHORE reanalysis) will be assessed.
Document type :
Poster communications
Complete list of metadata
Contributor : Administrateur IMT - Mines Alès Connect in order to contact the contributor
Submitted on : Monday, September 13, 2021 - 8:39:08 AM
Last modification on : Wednesday, November 24, 2021 - 3:56:17 PM


Files produced by the author(s)


  • HAL Id : hal-03341863, version 1


yann Visserot, Guillaume Artigue, Pierre-Alain Ayral, Audrey Bornancin-Plantier, Anne Johannet, et al.. Flood forecasting with machine Learning, data Assimilation and Semi-pHysical modeling. ERAD 2012 - The 7th European Conference on radar in Meteorology and Hydrology, Jun 2012, Toulouse, France. 35, pp.178 - 189, 2012. ⟨hal-03341863⟩



Record views


Files downloads